San Jose, CA, United States of America

Anand Kulkarni

This inventor holds 28 USPTO granted patents, primarily in Machine Learning Storage. Top assignees: Western Digital Technologies, Inc., Hitachi Global Storage Technologies Netherlands B.v., Sandisk Technologies Inc.. Active years: 2009-2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Anand Kulkarni. Retrieved from https://idiyas.com/inventor/anand-kulkarni

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 75.0

Average Co-Inventor Count = 3.2

ph-index = 9

Forward Citations = 245(Granted Patents)


Company Filing History:


Years Active: 2009-2025

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Areas of Expertise:
Feature Maps
Compute Core
Sparse Tensors
Convolutional Neural Networks
Non-Volatile Memory
Data Management
Storage Systems
Resource Management
Data Encryption
Virtual Storage
Garbage Collection
Binary Neural Networks
28 patents (USPTO):Explore Patents

Title: The Innovative Journey of Anand Kulkarni

Introduction: Anand Kulkarni, a talented inventor based in San Jose, CA, has made significant contributions to the field of technology through his groundbreaking innovations.

Latest Patents: Anand Kulkarni holds several patents in the areas of artificial intelligence, machine learning, and data analytics, showcasing his expertise in cutting-edge technologies.

Career Highlights: With a background in computer science and engineering, Anand Kulkarni has had a successful career working for leading tech companies, where he has spearheaded projects that have revolutionized the industry.

Collaborations: Throughout his career, Anand Kulkarni has collaborated with top researchers, engineers, and scientists to develop innovative solutions to complex technological challenges, further solidifying his reputation as a visionary inventor.

Conclusion: Anand Kulkarni's passion for innovation and his relentless pursuit of excellence continue to inspire the next generation of inventors and technologists.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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